Raw data from: Paddy farmers' awareness and knowledge of agroforestry practices in Siburan, Sarawak
Data files
Feb 19, 2025 version files 31.04 KB
Abstract
Rice is an important staple food, and the main source of income and livelihood especially for rural communities in Malaysia. However, the area under rice cultivation in Malaysia has decreased due to poor quality of rice fields due to low productivity and climate change. Agroforestry is a system that combines trees with crops or livestock. It not only counteracts the effects of climate change by increasing the resilience of agriculture, but also combats poverty, food security and land degradation. The aim of this study was to determine the awareness and perception of rice farmers in Siburan, Sarawak, towards agroforestry. The data for the study was obtained through questionnaire-based interviews in Kampung Skuduk and Kampung Chupak. Statistical tests were used to analyze and compare the data. Farmers’ knowledge of agroforestry practices was limited, especially among non-agroforestry practitioners. There is no significant income difference between agroforestry practitioners and non-agroforestry practitioners as agroforestry is practiced on a small scale and for household consumption as there are no commercial market opportunities for the products. Governmental or non-governmental organizations should organize educational activities on agroforestry to disseminate information on these practices appropriate to the education level and age group of the target farmers. Awareness raising and information dissemination activities are important as lack of awareness hinders the implementation of agroforestry, e.g. through awareness campaigns and training programs on agroforestry. The results of this study will serve as a guide for the authority to plan measures to increase the knowledge and importance of the agroforestry sector and the implementation of agroforestry.
https://doi.org/10.5061/dryad.cz8w9gjfh
Description of the data and file structure
The data collected focuses on paddy farmers in Siburan, Sarawak, and their awareness and knowledge of agroforestry practices. It encompasses various aspects, including the demographic characteristics of the respondents, reasons for practicing or not practicing agroforestry, and details on the specific agroforestry methods employed. Additionally, the data highlights the perceived benefits of agroforestry practices as recognized by the farmers and provides insights into their knowledge and perceptions of agroforestry. This comprehensive dataset aims to understand the level of awareness, adoption, and the challenges or motivations faced by paddy farmers regarding agroforestry practices in the region.
Files and variables
File: RAW_DATA-PADDY_FARMERS__AWARENESS_AND_KNOWLEDGE_OF_AGROFORESTRY_PRACTICES_IN_SIBURAN__SARAWAK.xlsx
Data Files
- Demographic\
Contains demographic details of respondents, including:- Respondents: Unique identifier for respondents.
- A2_VILLAGE: Village code.(1 = Chupak, 2 = Skuduk)
- A3_AGE: Age group (1 = 35-44, 2 = 45-54, 3 = 55-64, 4 = More than 65).
- A4_GENDER: Gender (1 = Male, 2 = Female).
- A5_MARRIAGE: Marital status (1 = Single, 2 = Married, 3 = Divorced/Widowed).
- A6_ETHNIC: Ethnic group code.(1 = Iban,2 = Bidayuh, 3 = Chinese, 4 = Orang Ulu, 5 = Others)
- A7_RELIGION: Religion code.(1 = Islam, 2 = Christian)
- A8_EDUCATION: Education level (1 = No formal education, 2 = Primary education, 3 = Secondary education 4 = Tertiary education).
- A9_HOUSEHOLD: Household size (0 = Not available, 1 = Less than 3, 2 = 4-6, 3 = 7-6, 4 = More than 10).
- A10_PADDY CULTIVATION FACTOR(X): Factors influencing paddy cultivation (1 = Main income, 2 = Extra income, 3 = Maintain the culture, 4 = Hobby, 5 = Maintain land ownership, 6 = Maintain the paddy breed).
- A11_STATUS AS PADDY FARMERS: Employment status as paddy farmers (1 = Full time, 2 = Part time).
- A12_OCCUPATION: Current occupation (0 = Not available, 1 = Government sector, 2 = Private sector, 3 = Self-employed).
- A13_MONTHLY INCOME: Monthly income range (1 = Less than RM1300, 2 = RM1301-RM1400, 3 = RM1401-RM1700, 4 = More than RM1700).
- A14_SIDE INCOME: Presence of side income (0 = Not available, 1 = Less than RM1300, 2 = RM1301-RM1400, 3 = RM1401-RM1700, 4 = More than RM1700 ).
- A15_PADDY CULTIVATION EXPERIENCE: Years of paddy cultivation experience (1 = Less tha 4 years, 2 = 5-10, 3 = 11-20, 4 = More than 21 years).
- Reason Practicing and Not Practicing\
Explores reasons for practicing or not practicing agroforestry:- RESPONDENTS: Unique identifier.
- C1_CONSUME: Rice for household comsumption (0 = Not available, 1 = Yes, 2 = No).
- C2_SELL: Selling rice (0 = Not available, 1 = Yes, 2 = No).
- C3_SELL EXTRA: Selling extra rice from comsumption (0 = Not available, 1 = Yes, 2 = No).
- C3_REASON: Reasons for selling (text).
- C4_YIELD: Yield performance (1 = Increase, 2 = Decrease, 3 = Same).
- C5_IN 5YRS: Continue to cultivate rice in 5 years (1 = Strongly agree, 2 = Agree, 3 = Not sure, 4 =Disagree,5 = Strongly disagree).
- C6_PROFITABLE: Perceived profitability of rice cultivation (1 = Strongly agree, 2 = Agree, 3 = Not sure, 4 =Disagree,5 = Strongly disagree).
- Practicing Agro\
Details on agroforestry practices:- RESPONDENTS: Unique identifier.
- D1_AGRO: Agroforestry participation (1 = Yes, 2 = No).
- D2_HEARD: Awareness of agroforestry (1 = Yes, 2 = No).
- D3_KNOWLEDGE: Level of knowledge (1 = very aware, 2 = aware, 3 = not sure, 4 = not aware, 5 = not aware at all).
- D4_BENEFITS: Awareness of benefits (1 = very aware, 2 = aware, 3 = not sure, 4 = not aware, 5 = not aware at all).
- D5_STARTED AGRO: Start of agroforestry practices (0 = Not available, 1 = Since started paddy cultivation, 2 = Few years after paddy cultivation, 3 = Lately).
- D6_INFLUENCES(X): Influences to start agroforestry (0 = Not available, 1 = Self-taught, 2 = Older generation, 3 = Friends, 4 = Media, 5 = Government agency, 6 = Non Government agency).
- D7_REASON(X): Reasons for participation (0 = Not available, 1 = Food source, 2 = Extra income, 3 = Others).
- D8_REASON NO AGRO(X): Reasons for not practicing (0 = Not available, 1 = Maintenance, 2 = Land access, 3 = Knowledge, 4 = Disturbing).
- D9_WANT TO AGRO: Interest in starting agroforestry (0 = Not available, 1 = Yes, 2 = No).
- Benefits of Agro\
Insights into perceived benefits of agroforestry:- RESPONDENTS: Unique identifier.
- D1_AGRO: Agroforestry participation ( 1 = Yes, 2 = No).
- E1_YIELD: Improvement in yield ( 1 = Yes, 2 = No).
- E2_SOIL FERTILITY: Impact on soil fertility ( 1 = Yes, 2 = No).
- E3_PEST: Pest control benefits ( 1 = Yes, 2 = No).
- E5_JOB OPPORTUNITY: Job opportunities created ( 1 = Yes, 2 = No).
- E6_FOOD SECURITY: Food security improvement ( 1 = Yes, 2 = No).
- E7_CLIMATE: Impact on climate resilience ( 1 = Yes, 2 = No).
- E8_EROSION: Reduction in soil erosion ( 1 = Yes, 2 = No).
- Knowledge and Perception\
Perceptions and recommendations related to agroforestry:- RESPONDENTS: Unique identifier.
- F1_BENEFITS: Perception of benefits (1 = Strongly agree, 2 = Agree, 3 = Not sure, 4 =Disagree,5 = Strongly disagree).
- F2_RECOMMEND: Willingness to recommend (1 = Strongly agree, 2 = Agree, 3 = Not sure, 4 = Disagree,5 = Strongly disagree).
- F3_INCREASE AGRICULTURE: Belief in increased agricultural productivity (1 = Strongly agree, 2 = Agree, 3 = Not sure, 4 =Disagree,5 = Strongly disagree).
- F4_PRACTICE IN AGRICULTURE: Practice level (1 = Strongly agree, 2 = Agree, 3 = Not sure, 4 = Disagree,5 = Strongly disagree).
- F5_AWARENESS ACTIVITY: Awareness activities participated (1 = Strongly agree, 2 = Agree, 3 = Not sure, 4 =Disagree,5 = Strongly disagree).
- F6_WORKSHOP SKILL: Workshop participation and skill enhancement (1 = Strongly agree, 2 = Agree, 3 = Not sure, 4 =Disagree,5 = Strongly disagree).
Variable Abbreviations and Definitions
- X: Placeholder for multiple related variables (e.g., D6_INFLUENCES1, D6_INFLUENCES2).
- Binary: 1 = Yes, 0 = No.
- Categorical: Ordinal or nominal scales.
- Numeric: Representing numeric values (e.g., age, household size, years).
Missing Values
- Missing data is indicated by:
- Blank cells.
- “NA” or zeros in categorical and binary variables.
Code/software
Software Description
- Name: Statistical Package for the Social Sciences (SPSS)
- Version Used: IBM SPSS Statistics Version 28 (or compatible versions)
Study area
This study was conducted in Kampung Skuduk and Kampung Chupak in Siburan District, Serian Division. Kg. Skuduk and Kg. Chupak is one of the wet paddy cultivation areas in Sarawak where rice is cultivated twice a year (Musa et al., 2021) and a successful pilot project for wet paddy cultivation (iM Sarawak ‘Wet Paddy Cultivation Program’) (Kong, 2014). The most important economic activity for the local population in Kg. Skuduk and Kg. Chupak is rice cultivation, according to the Siburan agricultural officer (personal communication). According to Jabatan Pertanian Daerah Siburan (Siburan District Department of Agriculture), there are about 89 rice farmers registered for 2023, most of whom are majority Bidayuh ethnic group and Christian.
Data collection
Data were collected through a formal questionnaire survey and interviews with registered rice farmers in Siburan. To ensure the representativeness of our sample, we collaborated with the Jabatan Pertanian Daerah Siburan (Siburan District Department of Agriculture) to identify a diverse group of respondents. Participants for this study were selected using purposive sampling to ensure the inclusion of individuals actively engaged in rice farming. This approach allowed us to focus on participants who could provide detailed insights into the practices, challenges, and knowledge associated with rice farming in the region. To achieve geographic and demographic diversity, we identified participants from different villages across the study area, considering factors such as age, farming experience, and land size.
The selection process aimed to capture a range of perspectives, ensuring representation of both small-scale and larger-scale farmers. Efforts were also made to balance educational levels within the sample by including participants with varying degrees of formal education. However, we acknowledge that the sample reflects the broader demographic trends of rice farmers in the region, where the majority tend to be older individuals. This age distribution aligns with regional statistics indicating that younger generations are less involved in traditional farming practices. The questionnaire contained open-ended questions that sought respondents’ opinions and closed-ended questions that included a menu of response options. The 5-point Likert scale was used to assess respondents’ knowledge, awareness and perception. The scales used in this study are (1 = very aware, 2 = aware, 3 = not sure, 4 = not aware, 5 = not aware at all) for knowledge and awareness.
The questionnaires consisted of seven sections: i) General socio-demographic information of the respondents; ii) General information on rice cultivation; iii) Respondents’ perception of rice cultivation; iv) Awareness and knowledge on agroforestry practices; v) Respondents’ awareness on the benefits of agroforestry; vi) Respondents’ perception on agroforestry practices; and vii) The challenges in adopting agroforestry practices. For this study, we categorized agroforestry practices to include both tree-based systems and annual crop intercropping systems. This inclusive categorization reflects the diverse agroecological strategies adopted by farmers in the study area. Farmers practicing tree-based agroforestry (e.g., rubber, fruit trees, or oil palm with rice) and non-tree-based intercropping (e.g., rice intercropped with maize or vegetables) were analysed under the broader agroforestry framework. This approach allows us to capture the spectrum of agroecological practices and better understand their socio-economic and environmental implications. The decision to stop conducting interviews was guided by the principle of data saturation. Data saturation occurs when no new themes, patterns, or significant insights emerge from additional interviews, indicating that further data collection is unlikely to contribute substantially to the research findings. In this study, saturation was reached after conducting approximately 43 interviews with paddy farmers. After the interview, the paddy field of the respondent agroforestry practitioners was visited to verify the information provided by the agroforestry practitioners and to determine the type of agroforestry practiced.
Data analysis
The data obtained from the interview and the questionnaires were analyzed using the Statistical Package for the Social Sciences (SPSS). An unpaired t-test was used to compare the data and find a significant difference between respondents practicing agroforestry and respondents not practicing agroforestry. Chi-square test of independence was used to determine the significant difference between agroforestry practitioners and non-agroforestry practitioners. Since farmers in the study area practice agroforestry on a small scale, agroforestry practitioners in this study are rice farmers who grow other crops near their rice field and non-agroforestry practitioners are farmers who grow only rice in the field. The data for the Likert scale on knowledge and awareness were analyzed according to the method of Alonazi et al. (2019). The weighted means were calculated for the Likert scales, from Strongly Agree=1 to Strongly Disagree=5, (Table 1) to determine the trend of the composite score (Alonazi et al. 2019). The weighted averages are calculated using the formula; Weighted mean = Σ(w)n (x̄)n/Σ(w)n. where, x̄ = the mean value of the set of given data. w = corresponding weight for each observation.